Article

Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

Wiley
British Journal of Management
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Abstract

Undertaking a review of the literature is an important part of any research project. The researcher both maps and assesses the relevant intellectual territory in order to specify a research question which will further develop the knowledge base. However, traditional 'narrative' reviews frequently lack thoroughness, and in many cases are not undertaken as genuine pieces of investigatory science. Consequently they can lack a means for making sense of what the collection of studies is saying. These reviews can be biased by the researcher and often lack rigour. Furthermore, the use of reviews of the available evidence to provide insights and guidance for intervention into operational needs of practitioners and policymakers has largely been of secondary importance. For practitioners, making sense of a mass of often-contradictory evidence has become progressively harder. The quality of evidence underpinning decision-making and action has been questioned, for inadequate or incomplete evidence seriously impedes policy formulation and implementation. In exploring ways in which evidence-informed management reviews might be achieved, the authors evaluate the process of systematic review used in the medical sciences. Over the last fifteen years, medical science has attempted to improve the review process by synthesizing research in a systematic, transparent, and reproducible manner with the twin aims of enhancing the knowledge base and informing policymaking and practice. This paper evaluates the extent to which the process of systematic review can be applied to the management field in order to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research. The paper highlights the challenges in developing an appropriate methodology.

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... SLRs offer a robust approach to analysing existing research, allowing us to synthesize diverse perspectives and identify areas requiring further investigation (Keele, 2007;Tranfield et al., 2003). This study leverages this strength to provide a comprehensive and future-oriented understanding of green entrepreneurship (Paul & Criado, 2020). ...
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... Specifically, we use a three-stage process in this study. As suggested by Tranfield et al. (2003) and Seuring and Müller (2008), these three steps are: (1) the material collection (the material to be collected is defined clearly); (2) the category selection (general aspects, e.g., publication year, research type, and specific aspects of the material to be assessed are selected); (3) the material evaluation (also called "content coding" and the analysis of the papers selected according to the categories defined in stage 2). ...
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... This study employs a systematic literature review approach following Tranfield et al. (2003), which is designed to enhance transparency, replicability, and rigour in synthesising existing knowledge. Systematic reviews are distinct from but related to structured literature reviews (Massaro et al., 2016). ...
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... Each article then underwent an initial screening process based on its title and abstract to assess its relevance to the research objectives. To ensure a rigorous content analysis, we established specific inclusion criteria, as recommended by Tranfield et al. (2003) and Denyer and Tranfield (2009). The criteria used for identifying and selecting papers are summarized in Table 2. Following these two screening stages, the number of relevant articles was narrowed down to 91, which were subsequently included for further analysis. ...
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... This paper adopted a simplified five-step systematic literature review according to the guidelines of Leonidou et al. (2020), Okoli (2015) and Perkmann et al. (2013). A systematic literature review is an important tool to achieve both accurate and reliable synthesis of evidence (Liberati et al., 2009), as well as transparent and replicable procedures (Tranfield et al., 2003;Okoli, 2005). This review includes five steps: question formulation, the definition of review protocols, application of review protocols, analysis of results (descriptive and thematic analysis), and data synthesis. ...
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Web of Scıence Veri Tabanı’nda İş Sağlığı ve Güvenliği Konusunda Yapılmış Akademik Çalışmaların Bibliyometrik Analizi İlhami AY Hatice ÖZDEMİR Murat DAL Mimari Tasarımda Sismik Dayanıklılık Üzerine Bibliyometrik Bir Analiz Arzu ER Mimarlık-Ergonomi İlişkisini Bilimsel Yayınlardan İzlemek: Bibliyometrik Bir İnceleme (1975-2025) Beyza Nur AZMANOĞLU İrem Zülal KARABİNA Şengül YALÇINKAYA Depreme Dayanıklı Kentleşmede Kentsel Dönüşüm ve Sürdürülebilirlik Uygulamalarının Rolü: Bibliyometrik Bir Analiz Sinem Helen UMUT Aslı ER AKAN Ulakbim Veri Tabanında Siber Güvenlik ve Denetim Konusunda Yayınlanmış Akademik Çalışmaların Bibliyometrik Analizi Ayşe Gül GÖK Spor Yönetimi Disiplininde Yapılmış Olan Doktora Tezlerinin Bibliyometrik Profili (2020-2024) Ali Gürel GÖKSEL Kaan ÇOLAKOĞLU Mustafa AKTOP Finansal Okuryazarlık Temelinin Oluşturulmasında Finansal Sosyalizasyon: Bibliometrik ve Sistematik Bir Analiz Adem ÖZBEK İklim Değişikliği ve Pazarlama: Web of Scıence Verilerıne Dayalı Bibliyometrik Bir Analiz (1985-2025) Ruhan İRİ
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This chapter provides a comprehensive analysis of the corporate reputation concept, examining its evolution and definitional challenges. It systematically reviews the literature from the past 50 years, categorizing studies into three distinct periods. It highlights the transition from viewing corporate reputation as a strategic asset to a relational approach focused on stakeholder perceptions and, more recently, to an integrative perspective that incorporates both. The chapter also discusses corporate reputation as a source of competitive advantage, drawing on theoretical frameworks such as the resource-based view, signalling theory, and institutional theory. Additionally, it explores corporate reputation’s classification as an intangible asset and the challenges associated with its measurement under accounting standards. By synthesizing various disciplinary perspectives and theoretical frameworks, this chapter sets the stage for subsequent discussions on reputation management and its impact on firms.
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The authors suggest that findings of independent, similar research articles may be aggregated into a cohesive study. Such a procedure greatly enhances the generalizability of the original studies and produces a relatively solid mid-range theory. In this article, the criteria for selecting studies, possible problems inherent in the aggregation approach, and potential areas for application are discussed.
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The explosion of knowledge production within business and other organizations poses a critical challenge to current modes of teaching and research within our business schools. We need to consider new strategic positions closer to the knowledge production being carried on within the organizations we study, without assuming that immediate relevance is our primary objective. The academic advantage, in my opinion, still lies in generalization and abstraction.
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A framework for synthesizing qualitative findings is described, and issues surrounding employment of this technique are discussed. Further debate on these issues is encouraged to develop and refine this framework. The practical importance of interpretive meta-synthesis is highlighted in relation to theory development.
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The past decade has witnessed widespread interest in the development of policy and practice that is better informed by evidence. Enthusiasm has, however, been tempered by recognition of the difficulties of devising effective strategies to ensure that evidence is integrated into policy and utilized in practice. There is already a rich but diverse and widely dispersed literature that can be drawn upon to inform such strategies. This article offers a guide to this literature by focusing on six main interrelated concerns: (1) the types of knowledge relevant to understanding research utilization/evidence-based practice (RU/EBP) implementation; (2) the ways in which research knowledge is utilized; (3) models of the process of utilization; (4) the conceptual frameworks that enable us to understand the process of RU/EBP implementation; (5) the main ways of intervening to increase evidence uptake and the effectiveness of these; (6) different ways of conceptualizing what RU/EBP means in practice.
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This is the first in a series of three articlesIn the past decade, qualitative methods have become more commonplace in areas such as health services research and health technology assessment, and there has been a corresponding rise in the reporting of qualitative research studies in medical and related journals.1 Interest in these methods and their wider exposure in health research has led to necessary scrutiny of qualitative research. Researchers from other traditions are increasingly concerned to understand qualitative methods and, most importantly, to examine the claims researchers make about the findings obtained from these methods.The status of all forms of research depends on the quality of the methods used. In qualitative research, concern about assessing quality has manifested itself recently in the proliferation of guidelines for doing and judging qualitative work.2–5 Users and funders of research have had an important role in developing these guidelines as they become increasingly familiar with qualitative methods, but require some means of assessing their quality and of distinguishing “good” and “poor” quality research. However, the issue of “quality” in qualitative research is part of a much larger and contested debate about the nature of the knowledge produced by qualitative research, whether its quality can legitimately be judged, and, if so, how. This paper cannot do full justice to this wider epistemological debate. Rather it outlines two views of how qualitative methods might be judged and argues that qualitative research can be assessed according to two broad criteria: validity and relevance. Summary points Qualitative methods are now widely used and increasingly accepted in health research, but quality in qualitative research is a mystery to many health services researchers There is considerable debate over the nature of the knowledge produced by such methods and how such research should be judged Antirealists argue …
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Introduction Remember the essays you used to write as a student? You would browse through the indexes of books and journals until you came across a paragraph that looked relevant, and copied it out. If anything you found did not fit in with the theory you were proposing, you left it out. This, more or less, constitutes the methodology of the journalistic review—an overview of primary studies which have not been identified or analysed in a systematic (standardised and objective) way. Summary points A systematic review is an overview of primary studies that used explicit and reproducible methods A meta-analysis is a mathematical synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way Although meta-analysis can increase the precision of a result, it is important to ensure that the methods used for the review were valid and reliable In contrast, a systematic review is an overview of primary studies which contains an explicit statement of objectives, materials, and methods and has been conducted according to explicit and reproducible methodology (fig 1). View larger version:In a new windowDownload as PowerPoint SlideFig 1 Methodology for a systematic review of randomised controlled trials1 Some advantages of the systematic review are given in box. When a systematic review is undertaken, not only must the search for relevant articles be thorough and objective, but the criteria used to reject articles as “flawed” must be explicit and independent of the results of those trials. The most enduring and useful systematic reviews, notably those undertaken by the Cochrane Collaboration, are regularly updated to incorporate new evidence.2 Box 1: Advantages of systematic reviews3 Explicit methods limit bias in identifying and rejecting studiesConclusions are more reliable and accurate because of methods usedLarge amounts of information can be assimilated quickly by healthcare providers, researchers, and policymakersDelay between research discoveries and implementation of effective diagnostic and therapeutic strategies may be reducedResults of different studies can be formally compared to establish generalisability of findings and consistency (lack of heterogeneity) of resultsReasons for heterogeneity (inconsistency in results across studies) can be identified and new hypotheses generated about particular subgroupsQuantitative systematic reviews (meta-analyses) increase the precision of the overall result RETURN TO TEXT Many, if not most, medical review articles are still written in narrative or journalistic form. Professor Paul Knipschild has described how Nobel prize winning biochemist Linus Pauling used selective quotes from the medical literature to “prove” his theory that vitamin C helps you live longer and feel better.3 4 When Knipschild and his colleagues searched the literature systematically for evidence for and against this hypothesis they found that, although one or two trials did strongly suggest that vitamin C could prevent the onset of the common cold, there were far more studies which did not show any beneficial effect. Experts, who have been steeped in a subject for years and know what the answer “ought” to be, are less able to produce an objective review of the literature in their subject than non-experts.5 6 This would be of little consequence if experts' opinions could be relied on to be congruent with the results of independent systematic reviews, but they cannot.7 Evaluating systematic reviews Question 1: Can you find an important clinical question which the review addressed? The question addressed by a systematic review needs to be defined very precisely, since the reviewer must make a dichotomous (yes/no) decision as to whether each potentially relevant paper will be included or, alternatively, rejected as “irrelevant.” Thus, for example, the clinical question “Do anticoagulants prevent strokes in patients with atrial fibrillation?” should be refined as an objective: “To assess the effectiveness and safety of warfarin-type anticoagulant therapy in secondary prevention (that is, following a previous stroke or transient ischaemic attack) in patients with non-rheumatic atrial fibrillation: comparison with placebo.”8 Question 2: Was a thorough search done of the appropriate databases and were other potentially important sources explored? Even the best Medline search will miss important papers, for which the reviewer must approach other sources.9 Looking up references of references often yields useful articles not identified in the initial search,10 and an exploration of “grey literature” (box) may be particularly important for subjects outside the medical mainstream, such as physiotherapy or alternative medicine.11 Finally, particularly where a statistical synthesis of results (meta-analysis) is contemplated, it may be necessary to write and ask the authors of the primary studies for raw data on individual patients which was never included in the published review. Box 2: Checklist of data sources for a systematic review Medline databaseCochrane controlled clinical trials registerOther medical and paramedical databasesForeign language literature“Grey literature” (theses, internal reports, non-peer reviewed journals, pharmaceutical industry files)References (and references of references, etc) listed in primary sourcesOther unpublished sources known to experts in the field (seek by personal communication)Raw data from published trials (seek by personal communication) RETURN TO TEXT Question 3: Was methodological quality assessed and the trials weighted accordingly? One of the tasks of a systematic reviewer is to draw up a list of criteria, including both generic (common to all research studies) and particular (specific to the field) aspects of quality, against which to judge each trial (see box). However, care should be taken in developing such scores since there is no gold standard for the “true” methodological quality of a trial12 and composite quality scores are often neither valid nor reliable in practice.13 14 The various Cochrane collaborative review groups are developing topic-specific methodology for assigning quality scores to research studies.15 Box 3: Assigning weight to trials in a systematic review Each trial should be evaluated in terms of its: Methodological quality—the extent to which the design and conduct are likely to have prevented systematic errors (bias)Precision—a measure of the likelihood of random errors (usually depicted as the width of the confidence interval around the result)External validity—the extent to which the results are generalisable or applicable to a particular target population RETURN TO TEXT Question 4: How sensitive are the results to the way the review has been done? Carl Counsell and colleagues “proved” (in the Christmas 1994 issue of the BMJ) an entirely spurious relationship between the result of shaking a dice and the outcome of an acute stroke.16 They reported a series of artificial dice rolling experiments in which red, white, and green dice represented different therapies for acute stroke. Overall, the “trials” showed no significant benefit from the three therapies. However, the simulation of a number of perfectly plausible events in the process of meta-analysis—such as the exclusion of several of the “negative” trials through publication bias, a subgroup analysis which excluded data on red dice therapy (since, on looking back at the results, red dice appeared to be harmful), and other, essentially arbitrary, exclusions on the grounds of “methodological quality”—led to an apparently highly significant benefit of “dice therapy” in acute stroke. If these simulated results pertained to a genuine medical controversy, how would you spot these subtle biases? You need to work through the “what ifs”. What if the authors of the systematic review had changed the inclusion criteria? What if they had excluded unpublished studies? What if their “quality weightings” had been assigned differently? What if trials of lower methodological quality had been included (or excluded)? What if all the patients unaccounted for in a trial were assumed to have died (or been cured)? View larger version:In a new windowDownload as PowerPoint Slide PETER BROWN An exploration of what ifs is known as a sensitivity analysis. If you find that fiddling with the data in various ways makes little or no difference to the review's overall results, you can assume that the review's conclusions are relatively robust. If, however, the key findings disappear when any of the what ifs changes, the conclusions should be expressed far more cautiously and you should hesitate before changing your practice in the light of them. Question 5: Have the numerical results been interpreted with common sense and due regard to the broader aspects of the problem? Any numerical result, however precise, accurate, “significant,” or otherwise incontrovertible, must be placed in the context of the painfully simple and often frustratingly general question which the review addressed. The clinician must decide how (if at all) this numerical result, whether significant or not, should influence the care of an individual patient. A particularly important feature to consider when undertaking or appraising a systematic review is the external validity or relevance of the trials that are included. Meta-analysis for the non-statistician A good meta-analysis is often easier for the non-statistician to understand than the stack of primary research papers from which it was derived. In addition to synthesising the numerical data, part of the meta-analyst's job is to tabulate relevant information on the inclusion criteria, sample size, baseline patient characteristics, withdrawal rate, and results of primary and secondary end points of all the studies included. Although such tables are often visually daunting, they save you having to plough through the methods sections of each paper and compare one author's tabulated results with another author's pie chart or histogram. These days, the results of meta-analyses tend to be presented in a fairly standard form, such as is produced by the computer software MetaView.3 is a pictorial representation (colloquially known as a “forest plot”) of the pooled odds ratios of eight randomised controlled trials which each compared coronary artery bypass grafting with percutaneous coronary angioplasty in the treatment of severe angina.17 The primary (main) outcome in this meta-analysis was death or heart attack within one year. View larger version:In a new windowDownload as PowerPoint SlideFig 2 Pooled odds ratios of eight randomised controlled trials of coronary artery bypass grafting against percutaneous coronary angioplasty, shown in MetaView format. Reproduced with authors' permission17 The horizontal line corresponding to each of the eight trials shows the relative risk of death or heart attack at one year in patients randomised to coronary angioplasty compared to patients randomised to bypass surgery. The “blob” in the middle of each line is the point estimate of the difference between the groups (the best single estimate of the benefit in lives saved by offering bypass surgery rather than coronary angioplasty), and the width of the line represents the 95% confidence interval of this estimate. The black line down the middle of the picture is known as the “line of no effect,” and in this case is associated with a relative risk of 1.0. If the confidence interval of the result (the horizontal line) crosses the line of no effect (the vertical line), that can mean either that there is no significant difference between the treatments or that the sample size was too small to allow us to be confident where the true result lies. The various individual studies give point estimates of the relative risk of coronary angioplasty compared with bypass surgery of between about 0.5 and 5.0, and the confidence intervals of some studies are so wide that they do not even fit on the graph. Now look at the tiny diamond below all the horizontal lines. This represents the pooled data from all eight trials (overall relative risk of coronary angioplasty compared with bypass surgery=1.08), with a new, much narrower, confidence interval of this relative risk (0.79 to 1.50). Since the diamond firmly overlaps the line of no effect, we can say that there is probably little to choose between the two treatments in terms of the primary end point (death or heart attack in the first year). Now, in this example, every one of the eight trials also suggested a non-significant effect, but in none of them was the sample size large enough for us to be confident in that negative result. Note, however, that this neat little diamond does not mean that you might as well offer coronary angioplasty rather than bypass surgery to every patient with angina. It has a much more limited meaning—that the average patient in the trials presented in this meta-analysis is equally likely to have met the primary outcome (death or myocardial infarction within a year), whichever of these two treatments they were randomised to receive. If you read the paper by Pocock and colleagues17 you would find important differences in the groups in terms of prevalence of angina and requirement for further operative intervention after the initial procedure. Explaining heterogeneity In the language of meta-analysis, homogeneity means that the results of each individual trial are mathematically compatible with the results of any of the others. Homogeneity can be estimated at a glance once the trial results have been presented in the format illustrated in figures 3 and 4. In 3 the lower confidence limit of every trial is below the upper confidence limit of all the others (that is, the horizontal lines all overlap to some extent). Statistically speaking, the trials are homogeneous. Conversely, in 4 some lines do not overlap at all. These trials may be said to be heterogeneous. View larger version:In a new windowDownload as PowerPoint SlideFig 3 Reduction in risk of heart disease by strategies for lowering cholesterol. Reproduced with permission from Chalmers and Altman18 The definitive test for heterogeneity involves a slightly more sophisticated statistical manoeuvre than holding a ruler up against the forest plot. The one most commonly used is a variant of the χ2 (chi square) test, since the question addressed is whether there is greater variation between the results of the trials than is compatible with the play of chance. Thompson18 offers the following rule of thumb: a χ2 statistic has, on average, a value equal to its degrees of freedom (in this case, the number of trials in the meta-analysis minus one), so a χ2 of 7.0 for a set of eight trials would provide no evidence of statistical heterogeneity. Note that showing statistical heterogeneity is a mathematical exercise and is the job of the statistician, but explaining this heterogeneity (looking for, and accounting for, clinical heterogeneity) is an interpretive exercise and requires imagination, common sense, and hands-on clinical or research experience. 4 shows the results of ten trials of cholesterol lowering strategies. The results are expressed as the percentage reduction in risk of heart disease associated with each reduction of 0.6 mmol/l in serum cholesterol concentration. From the horizontal lines which represent the 95% confidence intervals of each result it is clear, even without knowing the χ2 statistic of 127, that the trials are highly heterogeneous. Correcting the data for the age of the trial subjects reduced this value to 45. In other words, much of the “incompatibility” in the results of these trials can be explained by the fact that embarking on a strategy which successfully reduces your cholesterol level will be substantially more likely to prevent a heart attack if you are 45 than if you are 85. Clinical heterogeneity, essentially, is the grievance of Professor Hans Eysenck, who has constructed a vigorous and entertaining critique of the science of meta-analysis.19 In a world of lumpers and splitters, Eysenck is a splitter, and it offends his sense of the qualitative and the particular to combine the results of studies which were done on different populations in different places at different times and for different reasons. The articles in this series are excerpts from How to read a paper: the basics of evidence based medicine. The book includes chapters on searching the literature and implementing evidence based findings. It can be ordered from the BMJ Publishing Group: tel 0171 383 6185/6245; fax 0171 383 6662. Price £13.95 UK members, £14.95 non-members. Eysenck's reservations about meta-analysis are borne out in the infamously discredited meta-analysis which showed (wrongly) that giving intravenous magnesium to people who had had heart attacks was beneficial. A subsequent megatrial involving 58 000 patients (ISIS-4) failed to find any benefit, and the meta-analysts' misleading conclusions were subsequently explained in terms of publication bias, methodological weaknesses in the smaller trials, and clinical heterogeneity.20 21Acknowledgments Thanks to Professor Iain Chalmers for advice on this chapter. References1.↵The Cochrane Centre.Cochrane CollaborationHandbook [updated 9 December 1996]. The Cochrane Collaboration; issue 1. Oxford: Update Software, 1997.2.↵Bero L, Rennie D.The Cochrane Collaboration: preparing, maintaining, and disseminating systematic reviews of the effects of health care.JAMA 1995;274:1935–8.3.↵Chalmers I, Altman DG, eds. Systematic reviews. London: BMJ Publishing Group, 1995.4.↵Pauling L.How to live longer and feel better. New York: Freeman, 1986.5.↵Oxman AD, Guyatt GH.The science of reviewing research.Ann NY Acad Sci 1993;703: 125–31.6.↵Mulrow C.The medical review article: state of the science.Ann Intern Med 1987;106: 485–8.7.↵Antman EM, Lau J, Kupelnick B, Mosteller F, Chalmers TC.A comparison of results of meta-analyses of randomised controlled trials and recommendations of clinical experts.JAMA 1992;268: 240–8.8.↵Koudstaal P.Secondary prevention following stroke orTIA in patients with non-rheumatic atrial fibrillation: anticoagulant therapy versus control. Cochrane Database of Systematic Reviews. Oxford: Cochrane Collaboration, 1995. (Updated 14 February 1995.)9.↵Greenhalgh T.Searching the literature. In: How to read a paper. London: BMJ Publishing Group, 1997: 13–33.10.↵Chalmers I, Altman DGKnipschild P.Some examples of systematic reviews. In: Chalmers I, Altman DG.Systematic reviews. London: BMJ PublishingGroup, 1995: 9–16.11.↵Knipschild P.Searching for alternatives: loser pays. Lancet 1993;341: 1135–6.12.↵Oxman A, ed.Preparing and maintaining systematic reviews. In: Cochrane Collaboration handbook, section VI. Oxford: Cochrane Collaboration, 1995. (Updated 14 July 1995.)13.↵Emerson JD, Burdick E, Hoaglin DC, Mosteller F, Chalmers TC.An empirical study of the possible relation of treatment differences to quality scores in controlled randomized clinical trials.Controlled Clin Trials 1990;11: 339–52.14.↵Moher D, Jadad AR, Tugwell P.Assessing the quality of randomized controlled trials: current issues and future directions.IntJ Health Technol Assess 1996;12: 195–208.15.↵Garner P, Hetherington J.Establishing and supporting collaborative review groups. In: Cochrane Collaboration handbook, sectionII. Oxford: Cochrane Collaboration, 1995 (Updated 14 July 1995.)16.↵Counsell CE, Clarke MJ, Slattery J, Sandercock PAG.The miracle of DICE therapy for acute stroke: fact or fictional product of subgroup analysis?BMJ 1994;309: 1677–81.OpenUrlFREE Full Text17.↵Pocock SJ, Henderson RA, Rickards AF, Hampton JR, Sing SB III, Hamm CW, et al. Meta-analysis of randomised trials comparing coronary angioplasty with bypass surgery.Lancet 1995;346: 1184–9.18.↵Chalmers I, Altman DGThompson SG.Why sources of heterogeneity in meta-analysis should be investigated. In:Chalmers I, Altman DG.Systematicreviews. London, BMJ Publishing Group, 1995: 48–63.19.↵Chalmers I, Altman DGEysenck HJ.Problems with meta-analysis. In: Chalmers I, Altman DG.Systematic reviews. London: BMJ Publishing Group, 1995: 64–74.20.↵Magnesium, myocardial infarction, meta-analysis and mega-trials. Drug Ther Bull 1995;33: 25–7.21.↵Egger M, Davey Smith G.Misleading meta-analysis: lessons from “an effective, safe, simple” intervention that wasn't.BMJ 1995;310: 752–4.OpenUrlFREE Full Text
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This volume offers an exploration of major changes in the way knowledge is produced in science, technology, social science, & humanities, arguing that a new mode of knowledge production promises to replace or radically reform established institutions, disciplines, practices, & policies. A range of features - reflexivity, transdisciplinarity, heterogeneity - associated with the new mode of knowledge production are identified to illustrate the connections between them & the changing role of knowledge in social relations. Methodological difficulties inherent in attempts to describe a new mode of knowledge production are discussed, & implications of this mode for science policy & international economic competitiveness, collaboration, & globalization are treated. The book is particularly relevant for those concerned with educational systems, the changing nature of knowledge, the social study of science, & the connections between research & development, & social, economic, & technological development. The book is presented in 7 Chpts with a Preface & an Introduction. (1) Evolution of Knowledge Production. (2) The Marketability and Commercialisation of Knowledge. (3) Massification of Research and Education. (4) The Case of the Humanities. (5) Competitiveness, Collaboration and Globalisation. (6) Reconfiguring Institutions. (7) Towards Managing Socially Distributed Knowledge. References accompany each Chpt. 2 Tables. W. Howard (Copyright 1995, Sociological Abstracts, Inc., all rights reserved.)
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There has been an accumulation of qualitative studies in recent years, but little cumulation of the understandings gained from them. Qualitative research appears endangered both by efforts to synthesize studies and by the failure to do so. Techniques used have included reciprocal translations of key metaphors and concepts and qualitative and quantitative comparative analyses to produce narrative and theoretical integrations. The major problem yet to be resolved is developing usable and communicable systematic approaches to conducting metasynthesis projects that maintain the integrity of individual studies. © 1997 John Wiley & Sons, Inc. Res Nurs Health 20: 365–371, 1997
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